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At least 343 records · Page 19

Structure Slicing: Extending Logical Regions with Fields, In: SC '14: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis

Applications on modern supercomputers are increasingly limited by the cost of data movement, but mainstream programming systems have few abstractions for describing the structure of a program's data. Consequently, the burden of managing data movement, placement, and layout currently falls primarily upon the programmer. To address this problem we previously proposed a data model based on logical regions and described Legion, a programming system incorporating logical regions. In this paper, we present structure slicing, which incorporates fields into the logical region data model. We show that structure slicing enables Legion to automatically infer task parallelism from field non-interference, decouple the specification of data usage from layout, and reduce the overall amount of data moved. We demonstrate that structure slicing enables both strong and weak scaling of three Legion applications including S3D, a production combustion simulation that uses logical regions with thousands of fields, with speedups of up to 3.68X over a vectorized CPU-only Fortran implementation and 1.88X over an independently hand-tuned OpenACC code.

Computer Science↗

Conceptual Design of the Interaction Region Magnets for Future Electron-Ion Collider at Jefferson Lab

The Jefferson Lab Electron Ion Collider (JLEIC) is a proposed new machine for nuclear physics research. As proposed, it will deliver between 15 and 65 GeV center of mass energy collisions between electrons and nuclei. It uses the existing CEBAF accelerator as a full energy injector to deliver 3 to 10 GeV electrons into a new electron collider ring. An all new ion accelerator and collider complex will deliver up to 100 GeV protons, or 40 GeV/nucleon ions. The machine will have luminosity goals of above 1033 cm-2 sec-1 in the whole energy range with a maximum of a few 1034 cm-2 sec-1. The two collider rings use a unique figure-of eight layout to deliver a high degree of polarization in both beams. The machine will include room for two interaction regions with only one initially installed. The crossing angle in the primary interaction region will be 50 mrad. The whole detector region including forward detection covers about 80 meters of the JLEIC complex. This paper will describe the requirements and preliminary designs for both the ion and electron beam magnets in the most complex 32 m long interaction region (IR) around the interaction point (IP). The interaction region has over thirty-seven superconducting magnets operating at 4.5K; these include dipoles, quadrupoles, skew-quadrupoles, solenoids, horizontal and vertical correctors and higher order multipole magnets. The paper will also discuss the electromagnetic interaction between these magnets.

Wiseman, Mark (ORCID:0000000179110306)↗

A 4H Silicon Carbide Gate Buffer for Integrated Power Systems

A gate buffer fabricated in a 2-mu m 4H silicon carbide (SiC) process is presented. The circuit is composed of an input buffer stage with a push-pull output stage, and is fabricated using enhancement mode N-channel FETs in a process optimized for SiC power switching devices. Simulation and measurement results of the fabricated gate buffer are presented and compared for operation at various voltage supply levels, with a capacitive load of 2 nF. Details of the design including layout specifics, simulation results, and directions for future improvement of this buffer are presented. In addition, plans for its incorporation into an isolated high-side/low-side gate-driver architecture, fully integrated with power switching devices in a SiC process, are briefly discussed. This letter represents the first reported MOSFET-based gate buffer fabricated in 4H SiC.

Ericson, N↗

Concept Lens: Visual Comparison and Evaluation of Generative Model Manipulations

Generative models are becoming a transformative technology for the creation and editing of images. However, it remains challenging to harness these models for precise image manipulation. These challenges often manifest as inconsistency in the editing process, where both the type and amount of semantic change, depend on the image being manipulated. Moreover, there exist many methods for computing image manipulations, whose development is hindered by the matter of inconsistency. This paper aims to address these challenges by improving how we evaluate, compare, and explore the space of manipulations offered by a generative model. We present Concept Lens, a visual interface that is designed to aid users in understanding semantic concepts carried in image manipulations, and how these manipulations vary over generated images. Given the large space of possible images produced by a generative model, Concept Lens is designed to support the exploration of both generated images, and their manipulations, at multiple levels of detail. To this end, the layout of Concept Lens is informed by two hierarchies: a hierarchical organization of (1) original images, grouped by their similarities, and (2) image manipulations, where manipulations that induce similar changes are grouped together. This layout allows one to discover the types of images that consistently respond to a group of manipulations, and vice versa, manipulations that consistently respond to a group of codes. We show the benefits of this design across multiple use cases, specifically, studying the quality of manipulations for a single method, and offering a means of comparing different methods.

clustering↗

Reimagining Disassembly Interfaces With Visualization: Combining Instruction Tracing and Control Flow With DisViz

In applications where efficiency is critical, developers may examine their compiled binaries, seeking to understand how the compiler transformed their source code and what performance implications that transformation may have. This analysis is challenging due to the vast number of disassembled binary instructions and the many-to-many mappings between them and the source code. These problems are exacerbated as source code size increases, giving the compiler more freedom to map and disperse binary instructions across the disassembly space. Interfaces for disassembly typically display instructions as an unstructured listing or sacrifice the order of execution. Here, we design a new visual interface for disassembly code that combines execution order with control flow structure, enabling analysts to both trace through code and identify familiar aspects of the computation. Central to our approach is a novel layout of instructions grouped into basic blocks that displays a looping structure in an intuitive way. We add to this disassembly representation a unique block-based mini-map that leverages our layout and shows context across thousands of disassembly instructions. Finally, we embed our disassembly visualization in a web-based tool, DisViz, which adds dynamic linking with source code across the entire application. DizViz was developed in collaboration with program analysis experts following design study methodology and was validated through evaluation sessions with ten participants from four institutions. Participants successfully completed the evaluation tasks, hypothesized about compiler optimizations, and noted the utility of our new disassembly view. Our evaluation suggests that our new integrated view helps application developers in understanding and navigating disassembly code.

Computer science↗

Analysis and Optimization of a Multi-Layer Integrated Organic Substrate for High Current GaN HEMT-Based Power Module

In this paper, analysis and optimization of a multi-layer organic substrate for high current GaN HEMT based power module are discussed. The organic multi-layer substrates can provide high electrical performance in terms of low parasitic inductance in the power loop by providing vertical layout, and shielding for reduction of common-mode noise, a common problem in fast switching power converters. Furthermore, high performance cooling solutions, such as micro-channel heat sinks, can be directly bonded to the substrate for optimum thermal management. The structure of the proposed architecture, thermal analysis and optimization of layer thickness, thermo-mechanical stress analysis of the GaN HEMT and development of a high-performance heat sink are discussed.

47 OTHER INSTRUMENTATION↗

STUDY OF THE DESIGN REPRESENTATION METHODS FOR THE OPTIMIZATION OF MULTI-LAYER COMPOSITE STRUCTURES

The purpose of multi-layer composite structure optimization is to find the optimal composite layout, such that superior structure performances and lightweight can be achieved. However, the existing optimization methods have a low efficiency when applied to the multi-component, multi-layer composite structure. Such low efficiency is caused by the high dimensionality and the inherent shortcomings of the existing design representation methods. In this work, two composite layout representation methods are compared to better understand their impacts on optimization. The root cause of the low efficiency is identified, and its influences are also quantified using three metrics. Furthermore, a new Representation-Switch Optimization (RSO) strategy is proposed. This strategy improves the search efficiency by switching the design representation methods during the optimization process. Three benchmark studies, two mathematical examples and one real engineering example, are conducted to demonstrate the impact of design representation methods on the optimization results, as well as the effectiveness of the proposed optimization strategy.

Xu, Hongyi↗

Status Quo of Heliostat Field Deployment Processes

Deployment of the solar field of a concentrating solar power plant is one of many factors that are integral to the success of a project. Knowledge transfer from outside the industry is limited due to the unique nature of heliostats, which redirect sunlight to a receiver with high precision while maintaining a high level of reflectivity. Moreover, learning from project to project can be limited due to the site-specific nature of projects, as the market includes several developers, each with their own unique design. In this paper, we discuss the state of the art in heliostat field deployment. We cover all the key aspects of deployment from project assessment to a fully functioning system, which include site selection, layout development, supply chain, assembly, site preparation and construction, calibration, and operations and maintenance.

concentrating solar power↗

Design methodology: edgeless 3D ASICs with complex in-pixel processing for pixel detectors

The design methodology for the development of 3D integrated edgeless pixel detectors with in-pixel processing using Electronic Design Automation (EDA) tools is presented. A large area 3 tier 3D detector with one sensor layer and two ASIC layers containing one analog and one digital tier, is built for x-ray photon time of arrival measurement and imaging. A full custom analog pixel is 65μm x 65μm. It is connected to a sensor pixel of the same size on one side, and on the other side it has approximately 40 connections to the digital pixel. A 32 x 32 edgeless array without any peripheral functional blocks constitutes a sub-chip. The sub-chip is an indivisible unit, which is further arranged in a 6 x 6 array to create the entire 1.248cm x 1.248cm ASIC. Each chip has 720 bump-bond I/O connections, on the back of the digital tier to the ceramic PCB. All the analog tier power and biasing is conveyed through the digital tier from the PCB. The assembly has no peripheral functional blocks, and hence the active area extends to the edge of the detector. This was achieved by using a few flavors of almost identical analog pixels (minimal variation in layout) to allow for peripheral biasing blocks to be placed within pixels. The 1024 pixels within a digital sub-chip array have a variety of full custom, semi-custom and automated timing driven functional blocks placed together. The methodology uses a modified mixed-mode on-top digital implementation flow to not only harness the tool efficiency for timing and floor-planning but also to maintain designer control over compact parasitically aware layout. The methodology uses the Cadence design platform, however it is not limited to this tool.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SU-F-T-183: Design of a Beam Shaping Assembly of a Compact DD-Based Boron Neutron Capture Therapy System

Purpose: To design a beam shaping assembly (BSA) to shape the 2.45-MeV neutrons produced by a deuterium-deuterium (DD) neutron generator and to optimize the beam output for boron neutron capture therapy of brain tumors Methods: MCNP is used for this simulation study. The simulation model consists of a neutron surface source that resembles an actual DD source and is surrounded by a BSA. The neutron source emits 2.45-MeV neutrons isotropically. The BSA is composed of a moderator, reflector, collimator and filter. Various types of materials and geometries are tested for each component to optimize the neutron output. Neutron characteristics are measured with an 2×2×2-cm{sup 3} air-equivalent cylinder at the beam exit. The ideal BSA is determined by evaluating the in-air parameters, which include epithermal neutron per source neutron, fast neutron dose per epithermal neutron, and photon dose per epithermal neutron. The parameter values are compared to those recommended by the IAEA. Results: The ideal materials for reflector and thermal neutron filter were lead and cadmium, respectively. The thickness for reflector was 43 cm and for filter was 0.5 mm. At present, the best-performing moderator has 25 cm of AlF{sub 3} and 5 cm of MgF{sub 2}. This layout creates a neutron spectrum that has a peak at approximately 10 keV and produces 1.35E-4 epithermal neutrons per source neutron per cm{sup 2}. Additional neutron characteristics, fast neutrons per epithermal neutron and photon per epithermal neutron, are still under investigation. Conclusion: Working is ongoing to optimize the final layout of the BSA. The neutron spectrum at the beam exit window of the final configuration will have the maximum number of epithermal neutrons and limited photon and fast neutron contaminations within the recommended values by IAEA. Future studies will also include phantom experiments to validate the simulation results.

07 ISOTOPE AND RADIATION SOURCES↗

Mechanical assembly of complex, 3D mesostructures from releasable multilayers of advanced materials

Capabilities for assembly of three-dimensional (3D) micro/nanostructures in advanced materials have important implications across a broad range of application areas, reaching nearly every class of microsystem technology. Approaches that rely on the controlled, compressive buckling of 2D precursors are promising because of their demonstrated compatibility with the most sophisticated planar technologies, where materials include inorganic semiconductors, polymers, metals, and various heterogeneous combinations, spanning length scales from submicrometer to centimeter dimensions. We introduce a set of fabrication techniques and design concepts that bypass certain constraints set by the underlying physics and geometrical properties of the assembly processes associated with the original versions of these methods. In particular, the use of releasable, multilayer 2D precursors provides access to complex 3D topologies, including dense architectures with nested layouts, controlled points of entanglement, and other previously unobtainable layouts. Furthermore, the simultaneous, coordinated assembly of additional structures can enhance the structural stability and drive the motion of extended features in these systems. The resulting 3D mesostructures, demonstrated in a diverse set of more than 40 different examples with feature sizes from micrometers to centimeters, offer unique possibilities in device design. In conclusion, a 3D spiral inductor for near-field communication represents an example where these ideas enable enhanced quality ( Q ) factors and broader working angles compared to those of conventional 2D counterparts.

36 MATERIALS SCIENCE↗

Feasibility of crystal-assisted collimation in the CERN accelerator complex

Bent silicon crystals mounted on high-accuracy angular actuators were installed in the CERN Super Proton Synchrotron (SPS) and extensively tested to assess the feasibility of crystal-assisted collimation in circular hadron colliders. The adopted layout was exploited and regularly upgraded for about a decade by the UA9 Collaboration. The investigations provided the compelling evidence of a strong reduction of beam losses induced by nuclear inelastic interactions in the aligned crystals in comparison with amorphous orientation. A conceptually similar device, installed in the betatron cleaning insertion of CERN Large Hadron Collider (LHC), was operated through the complete acceleration and storage cycle and demonstrated a large reduction of the background leaking from the collimation region and radiated into the cold sections of the accelerator and the experimental detectors. The implemented layout and the relevant results of the beam tests performed in the SPS and in the LHC with stored proton and ion beams are extensively discussed.

43 PARTICLE ACCELERATORS↗

waveSZ: A Hardware-Algorithm Co-Design of Efficient Lossy Compression for Scientific Data

Error-bounded lossy compression is critical to the success of extreme-scale scientific research because of ever-increasing volumes of data produced by today's high-performance computing (HPC) applications. Not only can error-controlled lossy compressors significantly reduce the I/O and storage burden but they can retain high data fidelity for post analysis. Existing state-of-the-art lossy compressors, however, generally suffer from relatively low compression and decompression throughput (up to hundreds of megabytes per second on a single CPU core), which considerably restrict the adoption of lossy compression by many HPC applications especially those with a fairly high data production rate. In this paper, we propose a highly efficient lossy compression approach based on field programmable gate arrays (FPGAs) under the state-of-the-art lossy compression model SZ. Our contributions are fourfold. (1) We adopt a wavefront memory layout to alleviate the data dependency during the prediction for higher-dimensional predictors, such as the Lorenzo predictor. (2) We propose a co-design framework named WAVESZ based on the wavefront memory layout and the characteristics of SZ algorithm and carefully implement it by using high-level synthesis. (3) We propose a hardware-algorithm co-optimization method to improve the performance. (4) We evaluate our proposed WAVESZ on three real-world HPC simulation datasets from the Scientific Data Reduction Benchmarks and compare it with other state-of-the-art methods on both CPUs and FPGAs. Experiments show that our WAVESZ can improve SZ's compression throughput by 6.9x similar to 8.7x over the production version running on a state-of-the-art CPU and improve the compression ratio and throughput by 2.1x and 5.8x on average, respectively, respectively, compared with the state-of-the-art FPGA design.

Compression Ratio↗

Accelerating Random Forest Classification on GPU and FPGA

Random Forests (RFs) are a commonly used machine learning method for classification and regression tasks spanning a variety of application domains, including bioinformatics, business analytics, and software optimization. While prior work has focused primarily on improving performance of the training of RFs, many applications, such as malware identification, cancer prediction, and banking fraud detection, require fast RF classification. In this work, we accelerate RF classification on GPU and FPGA. In order to provide efficient support for large datasets, we propose a hierarchical memory layout suitable to the GPU/FPGA memory hierarchy. We design three RF classification code variants based on that layout, and we investigate GPU- and FPGA-specific considerations for these kernels. Our experimental evaluation, performed on an Nvidia Xp GPU and on a Xilinx Alveo U250 FPGA accelerator card using publicly available datasets on the scale of millions of samples and tens of features, covers various aspects. First, we evaluate the performance benefits of our hierarchical data structure over the standard compressed sparse row (CSR) format. Second, we compare our GPU implementation with cuML, a machine learning library targeting Nvidia GPUs. Third, we explore the performance/accuracy tradeoff resulting from the use of different tree depths in the RF. Finally, we perform a comparative performance analysis of our GPU and FPGA implementations. Our evaluation shows that for high accuracy targets, our GPU implementation yields 5-9x speedup over CSR, and up to a 2x speedup over cuML.

FPGA, Xilinx FPGA, GPU, Random Forest classificati↗

Realistic Cost to Execute Practical Quantum Circuits using Direct Clifford+T Lattice Surgery Compilation

We report a resource estimation pipeline that explicitly compiles quantum circuits expressed using the Clifford+T gate set into a surface code lattice surgery instruction set. The cadence of magic state requests from the compiled circuit enables the optimization of magic state distillation and storage requirements in a post-hoc analysis. To compile logical circuits into lattice surgery operations, we build upon the open-source Lattice Surgery Compiler. The revised compiler operates in two stages: the first translates logical gates into an abstract, layout-independent instruction set; the second compiles these into local lattice surgery instructions that are allocated to hardware tiles according to a specified resource layout. The second stage retains logical parallelism while avoiding resource contention in the fault-tolerant layer, aiding realism. Additionally, users can specify dedicated tiles at which magic states are replenished, enabling resource costs from the logical computation to be considered independently from magic state distillation and storage. We demonstrate the applicability of our pipeline to large practical quantum circuits by providing resource estimates for the ground state estimation of molecules. Finally, we find that variable magic state consumption rates in real circuits can cause the resource costs of magic state storage to dominate unless production is varied to suit.

97 MATHEMATICS AND COMPUTING↗

MemFriend: Understanding Memory Performance with Spatial-Temporal Affinity

In HPC applications, memory access behavior is one of the main factors affecting performance. Improving an application’s memory access behavior involves optimizing data layout and/or restructuring code, and requires studying spatial-temporal data locality. Existing data locality analyses focus on single-location metrics and are restricted to evaluating temporal locality. We introduce spatial-temporal affinity metrics that quantify temporal access proximity, forward access correlation, and nearby access correlation between pairs of memory locations. We describe methods for distinguishing between potential vs. realized affinity and for reasoning about affinity at multiple resolutions (3D, 2D, 1D). Finally, we construct spatial-temporal affinity signatures that classify memory behavior and that be used to reason about changes in software (data relayout, code refactoring) or hardware (caching, prefetching). We describe methods for signature visualization, interpretation, and quantitative comparison of signatures. We evaluate our methodology using applications with variants that contrast data structures, data layouts and algorithms. We show that spatial-temporal affinity analysis provides novel insights and enables predictive reasoning about application performance when contrasted with reuse distance analysis.

Suriyakumar, Yasodhadevi↗

NUMA-Aware Thread Scheduling for Big Data Transfers over Terabits Network Infrastructure

The evergrowing trend of big data has led scientists to share and transfer the simulation and analytical data across the geodistributed research and computing facilities. However, the existing data transfer frameworks used for data sharing lack the capability to adopt the attributes of the underlying parallel file systems (PFS). LADS (Layout-Aware Data Scheduling) is an end-to-end data transfer tool optimized for terabit network using a layout-aware data scheduling via PFS. However, it does not consider the NUMA (Nonuniform Memory Access) architecture. In this paper, we propose a NUMA-aware thread and resource scheduling for optimized data transfer in terabit network. First, we propose distributed RMA buffers to reduce memory controller contention in CPU sockets and then schedule the threads based on CPU socket and NUMA nodes inside CPU socket to reduce memory access latency. We design and implement the proposed resource and thread scheduling in the existing LADS framework. Experimental results showed from 21.7% to 44% improvement with memory-level optimizations in the LADS framework as compared to the baseline without any optimization.

97 MATHEMATICS AND COMPUTING↗

openPMD-viewer

Many simulation software produce data in the form of a set of field values or of a set of particle positions. (one such example is that of particle-in-cell codes, which produce data on the electromagnetic fields that they simulate.) However, each particular software uses its own particular format and layout, for the output data. This makes it difficult to compare the results of different simulation software, or to have a common visualization tool for these results. However, a standardized layout for fields and particles has recently been developed: the openPMD format ( HYPERLINK "http://www.openpmd.org/"www.openpmd.org) This format is open- source, and specifies a standard way in which field data and particle data should be written. The openPMD format is already implemented in the particle-in-cell code Warp (developed at LBL) and in PIConGPU (developed at HZDR, Germany). In this context, the proposed software (openPMD-viewer) is a Python package, which allows to access and visualize any data which has been formatted according to the openPMD standard. This package contains two main components: - a Python API, which allows to read and extract the data from a openPMD file, so as to be able to work with it within the Python environment. (e.g. plot the data and reprocess it with particular Python functions) - a graphical interface, which works with the ipython notebook, and allows to quickly visualize the data and browse through a set of openPMD files. The proposed software will be typically used when analyzing the results of numerical simulations. It will be useful to quickly extract scientific meaning from a set of numerical data.

Lehe, Remi↗